| Basin water resources have many applicable values and functions, such as flood control, power generation, water supply, navigation, irrigation and aquaculture. The way for rational development, utilization, conservation and protection of water resources as prevention of water disaster is a matter of global fundamental issues to scientific development, as well as a livelihood strategy. The water resources are very poor in China, exception highlighting on the water problem. With the development of industry and agriculture, as the improving live standards of urban and rural people, the contradiction between demand and supply of the water resources will become more serious. On the other hand, frequent extreme weather events during recent years further increase the complexity and uncertainty about the basin-water-resources management. Its primary objective is the way to use the water resources with minimal input from, financial and human resources to maximize social, economic and environmental benefits. Basin-water-resources system is a complex system under the effect on many aspects. Furthermore, the decision-making process of basin-water-resources management involved multiple areas, e.g. social, economic, hydrological, water flowing, hydraulic and ecological. Therefore, it is a typical half structure problem with multi-levels, multi-department and multi-objective properties. The traditional information management system cannot adapt the needs of modern basin-water-resources management. Based on the multidisciplinary decision-making operation unit, such as forecast, analysis, local search, and multi-objective multi-property decision-making, optimization, simulation, assessment, knowledge search, method and digital technology, which are defined as Model in this paper, decision support system will help the basin-water-resources manager to be carried out management better. Its key points are dynamic adaptability and heterogeneity. This article proposed a model-centric, two-tier loosely coupled iterative optimization structure with Behavior-optimized-ring and Technology-optimized-ring as the main feature. We define this new system as a Loose-coupling Model-driven Decision Support System, referred to LCMD-DSS, and propose its decision-making mechanism, system architecture and key technologies. For nearly four years, this method is widely applied to a large number of practical applications, represented by the973project. Compared with traditional solutions, we believe that this model-driven method is reasonable, reliable and flexible, thus has bright prospects of application for comprehensive basin-water-resources management. On the other hands, with the development of intellectual property protection and model application agreement, LCMD-DSS will greatly promote the advancement of the new learn-Institute-produced mode by combining the theory algorithm and actual engineering practice. It can provide theory and technology support for the science behavior to carry out basin-water-resources management work, as achieve the national strategy which titled Continued Using of Water Resource. This article’s main point of research and innovation are as follows:(1) Focusing the half-structure, multi-levels, multi-department and multi-objective properties of basin-water-resources management, we design a two-tier iterative optimization structure for continued integrated loose-coupling system, set up the division of the related roles, illustrate the loose-coupling technical framework through identifying and incorporating the key components, define our LCMD method and propose an architecture for designing;(2) Facing the integration challenges of LCMD-DSS, such as integrating of mass multi-source heterogeneous data, distributed open model gallery and based on GIS-based dynamic generated interactive platform. Using multi-discipline method, i.e. earth science, information science, computer science, space science, communications science, management science, economic, first, a uniform data platform (as Database Service) is presented to share multi-source data. Next, an open library (as Multidisciplinary Model Service) is presented to integrate cross-platform models. And, a universal linkage (as GIS Service) between GIS and models is presented by use of Service-oriented approach. Finally, a flexible interface system (as Interface Service) is presented to help practitioners customize the application for decision makers. They can provide technology support for two-tier loosely coupled iterative optimization structure of LCMD-DSS;(3) A well-balanced Godunov-type finite volume algorithm is developed for modeling free-surface shallow flows over irregular topography with complex geometry. The algorithm is based on a new formulation of the classical shallow-water equations in hyperbolic conservation form. Unstructured triangular grids are used to achieve the adaptability of the grid to the geometry of the problem and to facilitate localized refinement. The numerical fluxes are calculated using HLLC approximate Riemann solver, and the MUSCL-Hancock predictor-corrector scheme is adopted to achieve the second-order accuracy both in space and in time where the solutions are continuous, and to achieve high-resolution results where the solutions are discontinuous. The novelties of the algorithm include preserving well-balanced property without any additional correction terms and the wet/dry front treatments. It provides a platform for numerical simulation and visual simulation of basin-water-resources management stories;(4) Following the guide of new basin-water-resources management thought, the target of supporting water-administrative-sector to coordinate their work, the need of developing the general suitable decision support system, and the way to continued optimization LCMD method by the theory framework, referred to Behavior-optimized-ring, and technology library, referred to Technology-optimized-ring, the LCMD-DSS was employed to manage the basin-water-resources for experimental detection. |
PDF Full Text Request